Provided by: python-bumps_0.7.11-2_all bug


       bumps - data fitting and Bayesian uncertainty modeling for inverse problems


       bumps [options] modelfile [modelargs]

       bumps [{-? | -h | --help}]


       This manual page documents briefly the bumps command ( bumps3 for python3).

       This manual page was written for the Debian distribution because the original program does
       not have a manual page. Instead, it has documentation in HTML and in the GNU info(1)
       format; see below.

       bumps provides a set of routines for curve fitting and uncertainty analysis from a
       Bayesian perspective. In addition to traditional optimizers which search for the best
       minimum they can find in the search space, bumps provides uncertainty analysis which
       explores all viable minima and finds confidence intervals on the parameters based on
       uncertainty in the measured values. Bumps has been used for systems of up to 100
       parameters with tight constraints on the parameters. Full uncertainty analysis requires
       hundreds of thousands of function evaluations, which is only feasible for cheap functions,
       systems with many processors, or lots of patience.

       Bumps includes several traditional local optimizers such as Nelder-Mead simplex, BFGS and
       differential evolution. Bumps uncertainty analysis uses Markov chain Monte Carlo to
       explore the parameter space. Although it was created for curve fitting problems, Bumps can
       explore any probability density function, such as those defined by PyMC. In particular,
       the bumps uncertainty analysis works well with correlated parameters.

       The modelfile is a Python script (i.e., a series of Python commands) which sets up the
       data, the models, and the fittable parameters. The model arguments are available in the
       modelfile as sys.argv[1:]. Model arguments may not start with '-'.


       The program follows the usual GNU command line syntax, with long options starting with two
       dashes (`-'). A summary of options is included below. For a complete description, see the
       HTML documentation or info(1) files.

           display model but do not perform a fitting operation

           initial parameter values; fit results are saved as modelname.par

       --plot=log [linear|log|residuals]
           type of plot to display

           simulate a dataset using the initial problem parameters

           simulate a dataset using random problem parameters

           set random parameters before fitting

           percent noise to add to the simulated data

           random number seed

           show uncertainty estimate from curvature at the minimum

           show the covariance matrix for the model when done

           compute entropy for the model when done [dream only]

           output staj file when done

           start the gui

           one of the predefined problem views; reflectometry also has fresnel, logfresnel, q4
           and residuals

           output directory for plots and models

           if store already exists, replace it

       --resume=path [dream]
           resume a fit from previous stored state

           run fit using multiprocessing for parallelism

           run fit using MPI for parallelism (use command "mpirun -n cpus ...")

           batch mode; save output in .mon file and don't show plots after fit

           semi-batch; send output to console but don't show plots after fit

           queue fit to run on remote server

           remote fit notification

           remote job queue

           run for a maximum number of hours

       --fit=amoeba [amoeba|de|dream|lm|newton|ps|pt|rl|snobfit]
           fitting engine to use; see manual for details

       --steps=400 [amoeba|de|dream|lm|newton|ps|pt|rl|snobfit]
           number of fit iterations after any burn-in time

       --samples=1e4 [dream]
           set steps so the target number of samples is drawn

       --xtol=1e-4 [de, amoeba]
           minimum population diameter

       --ftol=1e-4 [de, amoeba]
           minimum population flatness

       --pop=10 [dream, de, rl, ps]
           population size

       --burn=100 [dream, pt]
           number of burn-in iterations before accumulating stats

       --thin=1 [dream]
           number of fit iterations between steps



       --Tmax=10 [pt]
           temperatures vector; use a higher maximum temperature and a larger nT if your fit is
           getting stuck in local minima

       --CR=0.9 [de, rl, pt]
           crossover ratio for population mixing

       --starts=1 [newton, rl, amoeba]
           number of times to run the fit from random starting points.

           when running with multiple starts, restart from a point near the last minimum rather
           than using a completely random starting point.

       --init=eps [dream]
           population initialization method:

               ball around initial parameter set

               latin hypercube sampling

               normally distributed according to covariance matrix

               uniformly distributed within parameter ranges

           show details for each step

           run resynthesis error analysis for n generations

           run the model --steps times in order to estimate total run time.

           run the python profiler on the model; use --steps to run multiple models for better

           print the model description and chisq value and exit

       -m, -c, -p command
           run the python interpreter with bumps on the path:

               command is a module such as bumps.cli, run as __main__

               command is a python one-line command

               command is the name of a python script

           start the interactive interpreter

       -?, -h, --help
           display this help


       Bumps is documented fully in HTML at /usr/share/doc/python-bumps-doc/html/index.html[1]
       and also in the info(1) system.


       Drew Parsons <>
           Wrote this manpage for the Debian system.


       Copyright © 2017 Drew Parsons

       This manual page was written for the Debian system (and may be used by others).

       Permission is granted to copy, distribute and/or modify this document under the terms of
       the GNU General Public License, Version 2 or (at your option) any later version published
       by the Free Software Foundation.

       On Debian systems, the complete text of the GNU General Public License can be found in


        1. /usr/share/doc/python-bumps-doc/html/index.html